Simple feature collection with 159 features and 8 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -85.60516 ymin: 30.35785 xmax: -80.84038 ymax: 35.00124
Geodetic CRS: NAD83
First 10 features:
GEOID NAME totalpopE totalpopM medincomeE medincomeM
1 13021 Bibb County, Georgia 156711 NA 43862 1778
2 13049 Charlton County, Georgia 12416 NA 45494 5791
3 13283 Treutlen County, Georgia 6410 NA 35441 9710
4 13309 Wheeler County, Georgia 7568 NA 26776 3605
5 13279 Toombs County, Georgia 26956 NA 42975 3095
6 13077 Coweta County, Georgia 144928 NA 83486 2974
7 13153 Houston County, Georgia 161177 NA 70313 3057
8 13183 Long County, Georgia 16398 NA 52742 8858
9 13163 Jefferson County, Georgia 15708 NA 42238 4150
10 13261 Sumter County, Georgia 29690 NA 36687 2163
medageE medageM geometry
1 36.2 0.3 MULTIPOLYGON (((-83.89192 3...
2 40.6 1.5 MULTIPOLYGON (((-82.4156 31...
3 39.9 5.3 MULTIPOLYGON (((-82.74762 3...
4 33.6 10.0 MULTIPOLYGON (((-82.93976 3...
5 37.8 0.9 MULTIPOLYGON (((-82.48038 3...
6 38.9 0.3 MULTIPOLYGON (((-85.0132 33...
7 35.9 0.3 MULTIPOLYGON (((-83.85685 3...
8 33.7 0.8 MULTIPOLYGON (((-81.98162 3...
9 40.5 0.8 MULTIPOLYGON (((-82.66192 3...
10 37.0 1.1 MULTIPOLYGON (((-84.44381 3...
#all counties in the USall_counties_withgeo <-get_acs(geography ="county",variables =c(myvars),output ="wide",geometry =TRUE)
Getting data from the 2017-2021 5-year ACS
Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.
all_counties_withgeo
Simple feature collection with 3221 features and 8 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -179.1489 ymin: 17.88328 xmax: 179.7785 ymax: 71.36516
Geodetic CRS: NAD83
First 10 features:
GEOID NAME totalpopE totalpopM medincomeE
1 20161 Riley County, Kansas 72602 NA 53296
2 19159 Ringgold County, Iowa 4739 NA 57700
3 30009 Carbon County, Montana 10488 NA 63178
4 16007 Bear Lake County, Idaho 6327 NA 60337
5 55011 Buffalo County, Wisconsin 13314 NA 61167
6 31185 York County, Nebraska 14164 NA 66337
7 08037 Eagle County, Colorado 55693 NA 91338
8 42129 Westmoreland County, Pennsylvania 355107 NA 64708
9 40079 Le Flore County, Oklahoma 48436 NA 43049
10 48053 Burnet County, Texas 48424 NA 65363
medincomeM medageE medageM geometry
1 2489 25.5 0.1 MULTIPOLYGON (((-96.96095 3...
2 5058 44.3 1.0 MULTIPOLYGON (((-94.47167 4...
3 4261 50.7 0.9 MULTIPOLYGON (((-109.7987 4...
4 7039 38.9 1.1 MULTIPOLYGON (((-111.6345 4...
5 2352 46.5 0.5 MULTIPOLYGON (((-92.08384 4...
6 4128 39.5 1.2 MULTIPOLYGON (((-97.82629 4...
7 4058 37.8 0.8 MULTIPOLYGON (((-107.1137 3...
8 1350 47.1 0.2 MULTIPOLYGON (((-79.90487 4...
9 1869 38.8 0.3 MULTIPOLYGON (((-95.05996 3...
10 4694 44.7 0.3 MULTIPOLYGON (((-98.45924 3...
#remove MOE columns - they all end with "M"ga_counties_withgeo <- ga_counties_withgeo %>%select(-ends_with("M"))ga_counties_withgeo
Simple feature collection with 159 features and 5 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -85.60516 ymin: 30.35785 xmax: -80.84038 ymax: 35.00124
Geodetic CRS: NAD83
First 10 features:
GEOID NAME totalpopE medincomeE medageE
1 13021 Bibb County, Georgia 156711 43862 36.2
2 13049 Charlton County, Georgia 12416 45494 40.6
3 13283 Treutlen County, Georgia 6410 35441 39.9
4 13309 Wheeler County, Georgia 7568 26776 33.6
5 13279 Toombs County, Georgia 26956 42975 37.8
6 13077 Coweta County, Georgia 144928 83486 38.9
7 13153 Houston County, Georgia 161177 70313 35.9
8 13183 Long County, Georgia 16398 52742 33.7
9 13163 Jefferson County, Georgia 15708 42238 40.5
10 13261 Sumter County, Georgia 29690 36687 37.0
geometry
1 MULTIPOLYGON (((-83.89192 3...
2 MULTIPOLYGON (((-82.4156 31...
3 MULTIPOLYGON (((-82.74762 3...
4 MULTIPOLYGON (((-82.93976 3...
5 MULTIPOLYGON (((-82.48038 3...
6 MULTIPOLYGON (((-85.0132 33...
7 MULTIPOLYGON (((-83.85685 3...
8 MULTIPOLYGON (((-81.98162 3...
9 MULTIPOLYGON (((-82.66192 3...
10 MULTIPOLYGON (((-84.44381 3...
#remove that trailing "E" for the state of GAcolnames(ga_counties_withgeo) <-sub("E$", "", colnames(ga_counties_withgeo)) # $ means end of string onlyga_counties_withgeo
Simple feature collection with 159 features and 5 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -85.60516 ymin: 30.35785 xmax: -80.84038 ymax: 35.00124
Geodetic CRS: NAD83
First 10 features:
GEOID NAM totalpop medincome medage
1 13021 Bibb County, Georgia 156711 43862 36.2
2 13049 Charlton County, Georgia 12416 45494 40.6
3 13283 Treutlen County, Georgia 6410 35441 39.9
4 13309 Wheeler County, Georgia 7568 26776 33.6
5 13279 Toombs County, Georgia 26956 42975 37.8
6 13077 Coweta County, Georgia 144928 83486 38.9
7 13153 Houston County, Georgia 161177 70313 35.9
8 13183 Long County, Georgia 16398 52742 33.7
9 13163 Jefferson County, Georgia 15708 42238 40.5
10 13261 Sumter County, Georgia 29690 36687 37.0
geometry
1 MULTIPOLYGON (((-83.89192 3...
2 MULTIPOLYGON (((-82.4156 31...
3 MULTIPOLYGON (((-82.74762 3...
4 MULTIPOLYGON (((-82.93976 3...
5 MULTIPOLYGON (((-82.48038 3...
6 MULTIPOLYGON (((-85.0132 33...
7 MULTIPOLYGON (((-83.85685 3...
8 MULTIPOLYGON (((-81.98162 3...
9 MULTIPOLYGON (((-82.66192 3...
10 MULTIPOLYGON (((-84.44381 3...
#Here is our initial mapview for the state of GAmapview(ga_counties_withgeo, zcol ="medincome")
# This set of code allows us to customize maps with colors. mapview(ga_counties_withgeo, zcol ="medincome", col.regions = RColorBrewer::brewer.pal(9, "Greens"), alpha.regions =1)
Warning: Found less unique colors (9) than unique zcol values (159)!
Interpolating color vector to match number of zcol values.